Side-by-side, with the numbers that matter.
Two rigs, one table. Higher numbers win in cobalt; TDP and price flip.
Rig A
AWS Trainium2
AWS · cloud-model
Change
- 1X Neo
- Agility Robotics Digit
- Alibaba Qwen2.5-72B-Instruct (Q4 quant)
- AMD Instinct MI300X
- AMD Instinct MI325X
- AMD Instinct MI355X
- Anthropic Claude Opus 4.7
- Apple Mac Pro (M2 Ultra, 2023)
- Apple Mac Studio (M3 Ultra)
- Apple MacBook Pro 16-inch, M4 Max (2024)
- Apptronik Apollo
- Aurora
- AWS Trainium2
- Boston Dynamics Atlas
- Boston Dynamics Spot
- Cerebras Wafer-Scale Engine 3
- El Capitan
- Figure 02
- Frontier (OLCF-5)
- Google Cloud TPU v5p
- Groq Language Processing Unit
- Intel Gaudi 3 HL-325L
- MSI GeForce RTX 5090 Suprim Liquid
- NVIDIA B100
- NVIDIA B200
- NVIDIA DGX B200
- NVIDIA DGX H200
- NVIDIA DGX Spark
- NVIDIA Eos DGX SuperPOD
- NVIDIA GB200
- NVIDIA GB200 NVL72
- NVIDIA GeForce RTX 4090 Founders Edition
- NVIDIA GeForce RTX 5070 Ti
- NVIDIA GeForce RTX 5080 Founders Edition
- NVIDIA GeForce RTX 5090 Founders Edition
- NVIDIA GH200 Grace Hopper
- NVIDIA H100
- NVIDIA H200
- NVIDIA HGX B200
- NVIDIA Jetson AGX Thor
- NVIDIA RTX PRO 4500 Blackwell
- NVIDIA RTX PRO 5000 Blackwell
- NVIDIA RTX PRO 6000 Blackwell
- OpenAI GPT-5
- SambaNova SN40L Reconfigurable Dataflow Unit
- Sanctuary AI Phoenix
- Tesla Optimus
- The Stargate Project
- Unitree B2
- Unitree G1
- Unitree H1
Rig B
Tesla Optimus
Tesla · edge
Change
- 1X Neo
- Agility Robotics Digit
- Alibaba Qwen2.5-72B-Instruct (Q4 quant)
- AMD Instinct MI300X
- AMD Instinct MI325X
- AMD Instinct MI355X
- Anthropic Claude Opus 4.7
- Apple Mac Pro (M2 Ultra, 2023)
- Apple Mac Studio (M3 Ultra)
- Apple MacBook Pro 16-inch, M4 Max (2024)
- Apptronik Apollo
- Aurora
- AWS Trainium2
- Boston Dynamics Atlas
- Boston Dynamics Spot
- Cerebras Wafer-Scale Engine 3
- El Capitan
- Figure 02
- Frontier (OLCF-5)
- Google Cloud TPU v5p
- Groq Language Processing Unit
- Intel Gaudi 3 HL-325L
- MSI GeForce RTX 5090 Suprim Liquid
- NVIDIA B100
- NVIDIA B200
- NVIDIA DGX B200
- NVIDIA DGX H200
- NVIDIA DGX Spark
- NVIDIA Eos DGX SuperPOD
- NVIDIA GB200
- NVIDIA GB200 NVL72
- NVIDIA GeForce RTX 4090 Founders Edition
- NVIDIA GeForce RTX 5070 Ti
- NVIDIA GeForce RTX 5080 Founders Edition
- NVIDIA GeForce RTX 5090 Founders Edition
- NVIDIA GH200 Grace Hopper
- NVIDIA H100
- NVIDIA H200
- NVIDIA HGX B200
- NVIDIA Jetson AGX Thor
- NVIDIA RTX PRO 4500 Blackwell
- NVIDIA RTX PRO 5000 Blackwell
- NVIDIA RTX PRO 6000 Blackwell
- OpenAI GPT-5
- SambaNova SN40L Reconfigurable Dataflow Unit
- Sanctuary AI Phoenix
- Tesla Optimus
- The Stargate Project
- Unitree B2
- Unitree G1
- Unitree H1
0 of 43 fields comparable
⇄ swap sides| Spec | AWS Trainium2 | Tesla Optimus |
|---|---|---|
| AI Stack | — | Tesla FSD-derived end-to-end neural networks (vision-only) |
| Battery KWH | — | 2.3 |
| Bf16 Tflops PER Chip | 667 | — |
| Chips PER Trn2 Instance | 16 | — |
| Chips PER Ultraserver | 64 | — |
| FP8 Dense Petaflops PER Chip | 1.3 | — |
| FP8 Sparse Petaflops PER Chip | 5.2 | — |
| Fremont Line Capacity Robots PER Year | — | 1,000,000 |
| Fremont Status Q2 2026 | — | S/X lines decommissioned; Optimus lines being installed |
| Gen2 Announcement Date | — | 2023-12-13 |
| Gen2 Hand DOF | — | 11 |
| Gen2 Height CM | — | 173 |
| Gen2 Neck DOF | — | 2 |
| Gen2 Total DOF Unverified | — | 28 |
| Gen2 Walking Speed Boost PCT | — | 30 |
| Gen2 Weight KG | — | 57 |
| Gen2 Weight Reduction KG | — | 10 |
| Gen3 Announcement Quarter | — | Q1 2026 |
| Gen3 Forearm Actuators | — | 25 |
| Gen3 Hand DOF | — | 22 |
| Gen3 Payload KG | — | 20 |
| Gen3 Production Target Superseded | — | summer 2026 |
| Gen3 Total Actuators PER Robot | — | 50 |
| Gen3 Unveil Status | — | not unveiled as of 2026-09-23 (Tesla North) |
| HBM Bandwidth TB S PER Chip | 2.9 | — |
| HBM Capacity GB PER Chip | 96 | — |
| HBM Type | HBM3 | — |
| Neuroncores PER Chip | 8 | — |
| Payload PER Hand KG | — | 9 |
| Public Sale Target | — | end of 2027 (Musk at Davos, 2026-01-22) |
| Runtime Hours Light Duty | — | 8 |
| Status Checked | — | 2026-09-24 |
| Trainium3 GA | 2025-12-02 | — |
| Trainium3 HBM Bandwidth TB S | 4.9 | — |
| Trainium3 Hbm3e GB PER Chip | 144 | — |
| Trn2 Instance FP8 Petaflops | 20.8 | — |
| Trn2 Instance HBM TB | 1.5 | — |
| Trn3 Ultraserver FP8 Pflops | 362 | — |
| Trn3 Ultraserver MAX Chips | 144 | — |
| Ultraserver FP8 Petaflops | 83.2 | — |
| Ultraserver Total HBM Bandwidth TB S | 185 | — |
| Ultraserver Total HBM TB | 6 | — |
| Walking Speed KM H | — | 8 |